LLVM Atomic Instructions and Concurrency Guide

Historically, LLVM has not had very strong support for concurrency; some
minimal intrinsics were provided, and volatile was used in some
cases to achieve rough semantics in the presence of concurrency. However, this
is changing; there are now new instructions which are well-defined in the
presence of threads and asynchronous signals, and the model for existing
instructions has been clarified in the IR.

The atomic instructions are designed specifically to provide readable IR and
optimized code generation for the following:

Other scenarios with atomic semantics, including static
variables with non-trivial constructors in C++.

Atomic and volatile in the IR are orthogonal; "volatile" is the C/C++
volatile, which ensures that every volatile load and store happens and is
performed in the stated order. A couple examples: if a
SequentiallyConsistent store is immediately followed by another
SequentiallyConsistent store to the same address, the first store can
be erased. This transformation is not allowed for a pair of volatile
stores. On the other hand, a non-volatile non-atomic load can be moved
across a volatile load freely, but not an Acquire load.

This document is intended to provide a guide to anyone either writing a
frontend for LLVM or working on optimization passes for LLVM with a guide
for how to deal with instructions with special semantics in the presence of
concurrency. This is not intended to be a precise guide to the semantics;
the details can get extremely complicated and unreadable, and are not
usually necessary.

The basic 'load' and 'store' allow a variety of
optimizations, but can lead to undefined results in a concurrent environment;
see NonAtomic. This section specifically goes
into the one optimizer restriction which applies in concurrent environments,
which gets a bit more of an extended description because any optimization
dealing with stores needs to be aware of it.

From the optimizer's point of view, the rule is that if there
are not any instructions with atomic ordering involved, concurrency does
not matter, with one exception: if a variable might be visible to another
thread or signal handler, a store cannot be inserted along a path where it
might not execute otherwise. Take the following example:

However, LLVM is not allowed to transform the former to the latter: it could
indirectly introduce undefined behavior if another thread can access x at
the same time. (This example is particularly of interest because before the
concurrency model was implemented, LLVM would perform this
transformation.)

Note that speculative loads are allowed; a load which
is part of a race returns undef, but does not have undefined
behavior.

For cases where simple loads and stores are not sufficient, LLVM provides
various atomic instructions. The exact guarantees provided depend on the
ordering; see Atomic orderings

load atomic and store atomic provide the same
basic functionality as non-atomic loads and stores, but provide additional
guarantees in situations where threads and signals are involved.

cmpxchg and atomicrmw are essentially like an
atomic load followed by an atomic store (where the store is conditional for
cmpxchg), but no other memory operation can happen on any thread
between the load and store. Note that LLVM's cmpxchg does not provide quite
as many options as the C++0x version.

A fence provides Acquire and/or Release ordering which is not
part of another operation; it is normally used along with Monotonic memory
operations. A Monotonic load followed by an Acquire fence is roughly
equivalent to an Acquire load.

Frontends generating atomic instructions generally need to be aware of the
target to some degree; atomic instructions are guaranteed to be lock-free,
and therefore an instruction which is wider than the target natively supports
can be impossible to generate.

In order to achieve a balance between performance and necessary guarantees,
there are six levels of atomicity. They are listed in order of strength;
each level includes all the guarantees of the previous level except for
Acquire/Release. (See also LangRef.)

NotAtomic is the obvious, a load or store which is not atomic. (This isn't
really a level of atomicity, but is listed here for comparison.) This is
essentially a regular load or store. If there is a race on a given memory
location, loads from that location return undef.

Relevant standard

This is intended to match shared variables in C/C++, and to be used
in any other context where memory access is necessary, and
a race is impossible. (The precise definition is in
LangRef.)

Notes for frontends

The rule is essentially that all memory accessed with basic loads and
stores by multiple threads should be protected by a lock or other
synchronization; otherwise, you are likely to run into undefined
behavior. If your frontend is for a "safe" language like Java,
use Unordered to load and store any shared variable. Note that NotAtomic
volatile loads and stores are not properly atomic; do not try to use
them as a substitute. (Per the C/C++ standards, volatile does provide
some limited guarantees around asynchronous signals, but atomics are
generally a better solution.)

Notes for optimizers

Introducing loads to shared variables along a codepath where they would
not otherwise exist is allowed; introducing stores to shared variables
is not. See Optimization outside
atomic.

Notes for code generation

The one interesting restriction here is that it is not allowed to write
to bytes outside of the bytes relevant to a store. This is mostly
relevant to unaligned stores: it is not allowed in general to convert
an unaligned store into two aligned stores of the same width as the
unaligned store. Backends are also expected to generate an i8 store
as an i8 store, and not an instruction which writes to surrounding
bytes. (If you are writing a backend for an architecture which cannot
satisfy these restrictions and cares about concurrency, please send an
email to llvmdev.)

Unordered is the lowest level of atomicity. It essentially guarantees that
races produce somewhat sane results instead of having undefined behavior.
It also guarantees the operation to be lock-free, so it do not depend on
the data being part of a special atomic structure or depend on a separate
per-process global lock. Note that code generation will fail for
unsupported atomic operations; if you need such an operation, use explicit
locking.

Relevant standard

This is intended to match the Java memory model for shared
variables.

Notes for frontends

This cannot be used for synchronization, but is useful for Java and
other "safe" languages which need to guarantee that the generated
code never exhibits undefined behavior. Note that this guarantee
is cheap on common platforms for loads of a native width, but can
be expensive or unavailable for wider loads, like a 64-bit store
on ARM. (A frontend for Java or other "safe" languages would normally
split a 64-bit store on ARM into two 32-bit unordered stores.)

Notes for optimizers

In terms of the optimizer, this prohibits any transformation that
transforms a single load into multiple loads, transforms a store
into multiple stores, narrows a store, or stores a value which
would not be stored otherwise. Some examples of unsafe optimizations
are narrowing an assignment into a bitfield, rematerializing
a load, and turning loads and stores into a memcpy call. Reordering
unordered operations is safe, though, and optimizers should take
advantage of that because unordered operations are common in
languages that need them.

Notes for code generation

These operations are required to be atomic in the sense that if you
use unordered loads and unordered stores, a load cannot see a value
which was never stored. A normal load or store instruction is usually
sufficient, but note that an unordered load or store cannot
be split into multiple instructions (or an instruction which
does multiple memory operations, like LDRD on ARM).

Monotonic is the weakest level of atomicity that can be used in
synchronization primitives, although it does not provide any general
synchronization. It essentially guarantees that if you take all the
operations affecting a specific address, a consistent ordering exists.

Relevant standard

This corresponds to the C++0x/C1x memory_order_relaxed;
see those standards for the exact definition.

Notes for frontends

If you are writing a frontend which uses this directly, use with caution.
The guarantees in terms of synchronization are very weak, so make
sure these are only used in a pattern which you know is correct.
Generally, these would either be used for atomic operations which
do not protect other memory (like an atomic counter), or along with
a fence.

Notes for optimizers

In terms of the optimizer, this can be treated as a read+write on the
relevant memory location (and alias analysis will take advantage of
that). In addition, it is legal to reorder non-atomic and Unordered
loads around Monotonic loads. CSE/DSE and a few other optimizations
are allowed, but Monotonic operations are unlikely to be used in ways
which would make those optimizations useful.

Notes for code generation

Code generation is essentially the same as that for unordered for loads
and stores. No fences are required. cmpxchg and
atomicrmw are required to appear as a single operation.

Acquire provides a barrier of the sort necessary to acquire a lock to access
other memory with normal loads and stores.

Relevant standard

This corresponds to the C++0x/C1x memory_order_acquire. It
should also be used for C++0x/C1x memory_order_consume.

Notes for frontends

If you are writing a frontend which uses this directly, use with caution.
Acquire only provides a semantic guarantee when paired with a Release
operation.

Notes for optimizers

Optimizers not aware of atomics can treat this like a nothrow call.
It is also possible to move stores from before an Acquire load
or read-modify-write operation to after it, and move non-Acquire
loads from before an Acquire operation to after it.

Notes for code generation

Architectures with weak memory ordering (essentially everything relevant
today except x86 and SPARC) require some sort of fence to maintain
the Acquire semantics. The precise fences required varies widely by
architecture, but for a simple implementation, most architectures provide
a barrier which is strong enough for everything (dmb on ARM,
sync on PowerPC, etc.). Putting such a fence after the
equivalent Monotonic operation is sufficient to maintain Acquire
semantics for a memory operation.

Release is similar to Acquire, but with a barrier of the sort necessary to
release a lock.

Relevant standard

This corresponds to the C++0x/C1x memory_order_release.

Notes for frontends

If you are writing a frontend which uses this directly, use with caution.
Release only provides a semantic guarantee when paired with a Acquire
operation.

Notes for optimizers

Optimizers not aware of atomics can treat this like a nothrow call.
It is also possible to move loads from after a Release store
or read-modify-write operation to before it, and move non-Release
stores from after an Release operation to before it.

Notes for code generation

See the section on Acquire; a fence before the relevant operation is
usually sufficient for Release. Note that a store-store fence is not
sufficient to implement Release semantics; store-store fences are
generally not exposed to IR because they are extremely difficult to
use correctly.

SequentiallyConsistent (seq_cst in IR) provides
Acquire semantics for loads and Release semantics for
stores. Additionally, it guarantees that a total ordering exists
between all SequentiallyConsistent operations.

Relevant standard

This corresponds to the C++0x/C1x memory_order_seq_cst,
Java volatile, and the gcc-compatible __sync_* builtins
which do not specify otherwise.

Notes for frontends

If a frontend is exposing atomic operations, these are much easier to
reason about for the programmer than other kinds of operations, and using
them is generally a practical performance tradeoff.

Notes for optimizers

Optimizers not aware of atomics can treat this like a nothrow call.
For SequentiallyConsistent loads and stores, the same reorderings are
allowed as for Acquire loads and Release stores, except that
SequentiallyConsistent operations may not be reordered.

Notes for code generation

SequentiallyConsistent loads minimally require the same barriers
as Acquire operations and SequentiallyConsistent stores require
Release barriers. Additionally, the code generator must enforce
ordering between SequentiallyConsistent stores followed by
SequentiallyConsistent loads. This is usually done by emitting
either a full fence before the loads or a full fence after the
stores; which is preferred varies by architecture.

isSimple(): A load or store which is not volatile or atomic. This is
what, for example, memcpyopt would check for operations it might
transform.

isUnordered(): A load or store which is not volatile and at most
Unordered. This would be checked, for example, by LICM before hoisting
an operation.

mayReadFromMemory()/mayWriteToMemory(): Existing predicate, but note
that they return true for any operation which is volatile or at least
Monotonic.

Alias analysis: Note that AA will return ModRef for anything Acquire or
Release, and for the address accessed by any Monotonic operation.

To support optimizing around atomic operations, make sure you are using
the right predicates; everything should work if that is done. If your
pass should optimize some atomic operations (Unordered operations in
particular), make sure it doesn't replace an atomic load or store with
a non-atomic operation.

Some examples of how optimizations interact with various kinds of atomic
operations:

memcpyopt: An atomic operation cannot be optimized into part of a
memcpy/memset, including unordered loads/stores. It can pull operations
across some atomic operations.

LICM: Unordered loads/stores can be moved out of a loop. It just treats
monotonic operations like a read+write to a memory location, and anything
stricter than that like a nothrow call.

DSE: Unordered stores can be DSE'ed like normal stores. Monotonic stores
can be DSE'ed in some cases, but it's tricky to reason about, and not
especially important.

Folding a load: Any atomic load from a constant global can be
constant-folded, because it cannot be observed. Similar reasoning allows
scalarrepl with atomic loads and stores.

Atomic operations are represented in the SelectionDAG with
ATOMIC_* opcodes. On architectures which use barrier
instructions for all atomic ordering (like ARM), appropriate fences are
split out as the DAG is built.

The MachineMemOperand for all atomic operations is currently marked as
volatile; this is not correct in the IR sense of volatile, but CodeGen
handles anything marked volatile very conservatively. This should get
fixed at some point.

Common architectures have some way of representing at least a pointer-sized
lock-free cmpxchg; such an operation can be used to implement
all the other atomic operations which can be represented in IR up to that
size. Backends are expected to implement all those operations, but not
operations which cannot be implemented in a lock-free manner. It is
expected that backends will give an error when given an operation which
cannot be implemented. (The LLVM code generator is not very helpful here
at the moment, but hopefully that will change.)

The implementation of atomics on LL/SC architectures (like ARM) is currently
a bit of a mess; there is a lot of copy-pasted code across targets, and
the representation is relatively unsuited to optimization (it would be nice
to be able to optimize loops involving cmpxchg etc.).

On x86, all atomic loads generate a MOV.
SequentiallyConsistent stores generate an XCHG, other stores
generate a MOV. SequentiallyConsistent fences generate an
MFENCE, other fences do not cause any code to be generated.
cmpxchg uses the LOCK CMPXCHG instruction.
atomicrmw xchg uses XCHG,
atomicrmw add and atomicrmw sub use
XADD, and all other atomicrmw operations generate
a loop with LOCK CMPXCHG. Depending on the users of the
result, some atomicrmw operations can be translated into
operations like LOCK AND, but that does not work in
general.

On ARM, MIPS, and many other RISC architectures, Acquire, Release, and
SequentiallyConsistent semantics require barrier instructions
for every such operation. Loads and stores generate normal instructions.
cmpxchg and atomicrmw can be represented using
a loop with LL/SC-style instructions which take some sort of exclusive
lock on a cache line (LDREX and STREX on
ARM, etc.). At the moment, the IR does not provide any way to represent a
weak cmpxchg which would not require a loop.